# Model Deployment & Inferencing

This section covers the various environments where SEA-LION models can be hosted, ranging from fully managed cloud services to self-hosted high-performance infrastructure. SEA-LION models are freely available for [download](https://docs.sea-lion.ai/models/download_models). The following guides provide technical how-tos for setting up SEA-LION inference using different approaches:

1. [Using our provided SEA-LION API](https://docs.sea-lion.ai/guides/inferencing/api)
2. Running SEA-LION on a local machine (coming soon)
3. Deploying SEA-LION on the cloud
   * [Create SEA-LION endpoint on Google Vertex AI](https://docs.sea-lion.ai/guides/inferencing/vertex_ai)
   * [Importing and Using Llama-SEA-LION models in a Serverless On-Demand Environment with Amazon Bedrock](https://docs.sea-lion.ai/guides/inferencing/amazon_bedrock)
   * [OpenAI-compatible APIs with Llama-SEA-LION models and Bedrock Access Gateway](https://docs.sea-lion.ai/guides/inferencing/bedrock_access_gateway)
   * [Deploying Gemma-SEA-LION models using AWS Sagemaker AI](https://github.com/aisingapore/sealion/blob/main/guides/inferencing/Gemma-SEA-LION-v4-27B-Instruct.ipynb)
   * [Deploying SEA-LION using vLLM on Linux server](https://docs.sea-lion.ai/guides/inferencing/vllm_linux)
4. Leveraging our Partner API Platforms
   * [Cloudflare Workers AI](https://docs.sea-lion.ai/guides/inferencing/cloudflare)